Top Machine Learning Jobs in Seattle, WA

The Senior Machine Learning Platform Engineer will build foundational components for ML models, mentor junior engineers, and optimize streaming pipelines. Responsibilities include enhancing ML infrastructure and ensuring data quality.

The Senior Applied Scientist II is responsible for designing and implementing ML models to optimize the supply chain, collaborating across teams, and driving data-driven decision-making.

The Senior Machine Learning Engineer will develop ML APIs, build data pipelines, and collaborate across teams to enhance ML models and applications.

Lead the development and implementation of machine learning solutions, managing a team to drive strategic decisions and innovative business outcomes.

Lead the design, development, and deployment of foundational ML systems, influence architecture, mentor engineers, and drive strategic initiatives within SailPoint's AI team.

The Senior Machine Learning Engineer will design, implement, and optimize machine learning models, drive AI initiatives, and collaborate cross-functionally to enhance SailPoint's AI capabilities.

The Principal Applied ML Researcher will define ML and LLM strategies for Trase OS, lead technical breakthroughs, manage the research-to-production lifecycle, and ensure reliable systems deployment in regulated environments.

As a Software Engineering Intern, you will contribute to building features for user-facing products, APIs, and scalable services for machine learning. Responsibilities include crafting code, designing data pipelines, implementing tools, and enhancing technical documentation.

The role involves building predictive models for blockchain performance and user behavior, implementing solutions, and owning production prediction pipelines.

The VP of Ads Quality Engineering will lead the AI/ML engineering team to improve Pinterest's ads delivery and monetization strategies, collaborating with various departments to develop innovative solutions using machine learning.

The Principal ML Engineer at Agero will develop and productionize a Dispatch System using ML models, optimize decision-making processes, and lead a team to improve operational performance.

Lead machine learning initiatives to enhance underwriting model accuracy. Design and implement advanced training strategies and optimize workflows. Mentor engineers and influence modeling strategy.

As a Forward Deployed Machine Learning Engineer, you'll build and deploy machine learning models, enhance system performance, and collaborate with Data Science and Engineering teams for effective solutions.

The Machine Learning Engineer will work on unstructured data classification and clustering, utilizing their expertise in AI systems and various programming languages.

The Senior Machine Learning Engineer will utilize deep experience and insights to enhance communication and digital interactions through advanced machine learning tools and algorithms, focusing on unstructured data.

Lead development and production deployment of advanced ML and time-series models for water and infrastructure systems, perform research in Physical AI, collaborate cross-functionally, communicate impact to stakeholders, and mentor junior data scientists.

As an Applied Scientist II, you will work with cross-functional teams on projects that optimize software systems and improve ML components, while analyzing inefficiencies and proposing solutions.

Design, develop, and deliver machine learning models for clinical data. Collaborate with stakeholders and optimize production ML systems.

Lead the machine learning strategy, design scalable ML systems, drive MLOps, mentor engineers, and comply with AI governance.

Lead the development of production-grade machine learning systems, build ML pipelines, and optimize models for deployment and performance.

Lead the Applied Machine Learning team at ExtraHop to develop systems for behavioral detection in network security. Manage model design, evaluation, and operationalization while maintaining experimental rigor and collaborating with product teams.

As a Senior Machine Learning Engineer, you will design and build ML models for patient-provider matching, focusing on personalization and ranking. Responsibilities include model development, A/B testing, and collaborating across teams to improve patient experiences.

The Staff Machine Learning Engineer will lead ML systems development for personalization and ranking, design architectures, and mentor team members, ensuring reliable operations at scale.

The Principal Machine Learning Engineer will design and scale ML systems for personalization and search, mentor engineers, and lead major ML initiatives at Fetch.

The Director of Machine Learning Engineering is responsible for leading AI strategy, overseeing ML solutions, driving innovation, building teams, and ensuring operational excellence in ML systems.